What’s going on with this data?

This report analyses patterns and trends in relevant advertisements. The data used in this report was collected from a Google form based on observational logging, where participants recorded their encounters with digital advertisements. These observations include information such as the advertisement platform, advertisement format, number of products in the advertisement, whether the advertisement is relevant to the respondents and the duration of interaction. This form had a mixture of questions that generated numerical and categorical data. All responses were self-reported. Some of this data has been used to create visualisations to uncover meaningful insights, such as which platform has more relevant advertisements, which format has more relevant advertisements and to determine whether the number of relevant advertisements increases over time.

Social Media Platforms shown on a phone held by a person
Social Media Platforms shown on a phone held by a person

Plot 1: Different Platform More Relevant Advertisements?

Bar chart showing the distribution of advertisements across different platforms. The bars represent the number of ads, with each platform divided into categories based on how relevant they were considered (Maybe, Yes, No). The count of ads is displayed above each bar for clarity.
Bar chart showing the distribution of advertisements across different platforms. The bars represent the number of ads, with each platform divided into categories based on how relevant they were considered (Maybe, Yes, No). The count of ads is displayed above each bar for clarity.

The bar chart above visualises the number of advertisements across various platforms and categorises them by how relevant users consider them. This analysis helps us understand trends, such as whether specific platforms show relevant ads more often than others. The plot above shows that Instagram has the most Relevant Ads (26), whereas all the platforms combined have 16 Relevant Ads. Reddit was the only platform for which the number of ads not relevant was higher than the number of ads relevant and the number of ads possibly relevant. From this data, we can say that Instagram has the most relevant ads. Thus, businesses may opt to use Instagram for better targeted ads, or users may opt to use Instagram for more personalised ads. However, since the data was collected through observational logging via a single person, we need to consider the possibility of the data being biased as the individual may use Instagram more than the other platforms.

Plot 2: Relevant Advertisements

Bar chart showing the number of relevant advertisements with time spent longer than 20 seconds, grouped by ad format (GIF/s, Images/s, Video/s) and split between Facebook and Instagram platforms.
Bar chart showing the number of relevant advertisements with time spent longer than 20 seconds, grouped by ad format (GIF/s, Images/s, Video/s) and split between Facebook and Instagram platforms.

The bar chart above shows the number of relevant advertisements that users spent time on for more than 20 seconds, broken down by ad format and split between the Facebook and Instagram platforms. Facebook and Instagram were selected as they were used the most (as seen in plot 1). Instagram’s relevant ads on which users spent time for more than 20 seconds consisted of 3 formats: GIF/s, Image/s and Video/s. Facebook’s only had 4 relevant ads on which users spent time for more than 20 seconds and all of them were images. From this we can say that Instagram is the most versatile platform allowing different formats of advertisements and aiming it towards the right audience. From this we can say that businesses may opt to use Instagram for advertisements regardless of the format of their advertisement as Instagram will be more successful in showing it to the right audience and retaining the audience for longer periods. We once again need to consider the possibility of the data being biased as the individual may use Instagram more than the other platforms.

Plot 3: Does the number of Relevant Advertisements increase over time?

Line graph displaying the weekly number of advertisements grouped by relevance (Yes, No, Maybe). Start and end values are labeled for each relevance category.
Line graph displaying the weekly number of advertisements grouped by relevance (Yes, No, Maybe). Start and end values are labeled for each relevance category.

The line graph above shows how the number of ads perceived as “relevant,” “not relevant,” or “possibly relevant” varied across weeks. Each line represents a different relevance category, and the data points are grouped weekly to highlight trends over time. For the Relevant Ads, the number of ads dipped slightly from the beginning value of 23 to the ending value of 19. For the Irrelevant Ads, the number of ads dropped from 15 to 8. For advertisements that may be relevant, the number of ads increased from the beginning value of 4 to the ending value of 9. Although we can not determine a clear pattern straight away, we can predict that as the weeks go by, the platforms are able to better target advertisements that are relevant to the user, as seen with the increase in relevant ads and a dip in irrelevant ads. We once again need to consider the possibility of the data being biased, as the individual may have filled the form more often on certain weeks.